Model 2 analysis
Benjamin Mercier
Last updated on 13 October, 2022
Model 2
Description of the model
This second model is a slight variant of the first, in which we assign a specific \(\alpha\) to each predator. In doing so, we can isolate difference between predator, to check if some predator seems to be different from the whole. \[\begin{align}
F_{ij}^{real} &= \alpha_{j} * B_i * \frac{B_j}{M_j}
\end{align}\]
This model was fit with a hierarchy implemented on the alpha parameter. A global alpha was estimated, with 118 respective unique alphas for each predators.
Summary table
| mean | se_mean | sd | 2.5% | 25% | 50% | 75% | 97.5% | n_eff | Rhat | |
|---|---|---|---|---|---|---|---|---|---|---|
| a_pop | -11.372587 | 0.0126132 | 0.3472806 | -12.062460 | -11.596693 | -11.377177 | -11.146692 | -10.688059 | 758.0769 | 1.0075681 |
| a_sd | 3.618977 | 0.0016733 | 0.2459876 | 3.180096 | 3.448036 | 3.604867 | 3.775383 | 4.133089 | 21612.1144 | 0.9998206 |
| sigma | 1.690426 | 0.0002914 | 0.0408437 | 1.613122 | 1.662297 | 1.689411 | 1.717868 | 1.773246 | 19648.2965 | 0.9997805 |
Exploring parameters posterior distribution
General parameters
Respective predator alphas
Rhats
Examining Rhats to see if all parameters have converge
Simulated data vs observed data
